Recent advances of muconic acid production using microbial synthetic biology

IF 2.6 3区 生物学 Q3 MICROBIOLOGY
Xiqiang Liu, Jintao Lu, Siqi Chen, Mingyang Wang, Aamer Ali Shah, Chunjie Gong
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引用次数: 0

Abstract

Muconic acid is a high-value intermediate with unique properties. Traditional methods for muconic acid production showed some disadvantages including expensive raw materials, environmentally sensitive, and high concentration of heavy metal catalysts. With the development of synthetic biology, bio-strategies for muconic acid production have been widely studied. In this paper, key advances in muconic acid production using synthetic biology are highlighted. Furthermore, strategies for improving muconic acid production have been discussed, including cofactor engineering, modular co-culture, and artificial intelligence-assisted enzyme optimization. Given the significant advantages of biosynthesis in clean production and cost control, the paper concludes with an analysis of the economic and technical feasibility of microbial muconic acid production.

利用微生物合成生物学生产粘膜酸的研究进展
麝香酸是一种具有独特性能的高价值中间体。传统生产黏膜酸的方法存在原料昂贵、环境敏感、重金属催化剂浓度高等缺点。随着合成生物学的发展,合成乳酸菌酸的生物策略得到了广泛的研究。本文重点介绍了利用合成生物学生产乳酸菌酸的研究进展。此外,还讨论了提高粘膜酸产量的策略,包括辅因子工程、模块化共培养和人工智能辅助酶优化。鉴于生物合成在清洁生产和成本控制方面的显著优势,本文最后分析了微生物生产乳酸菌酸的经济和技术可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Archives of Microbiology
Archives of Microbiology 生物-微生物学
CiteScore
4.90
自引率
3.60%
发文量
601
审稿时长
3 months
期刊介绍: Research papers must make a significant and original contribution to microbiology and be of interest to a broad readership. The results of any experimental approach that meets these objectives are welcome, particularly biochemical, molecular genetic, physiological, and/or physical investigations into microbial cells and their interactions with their environments, including their eukaryotic hosts. Mini-reviews in areas of special topical interest and papers on medical microbiology, ecology and systematics, including description of novel taxa, are also published. Theoretical papers and those that report on the analysis or ''mining'' of data are acceptable in principle if new information, interpretations, or hypotheses emerge.
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